Protein contact map prediction using multi-stage hybrid intelligence inference systems

Journal of Biomedical Informatics

Volumn 45, Issue 1, 2012, Pages 173-183

  Abu Doleh, Anas A ^a   Al Jarrah, Omar M ^a   Alkhateeb, Asem ^a  

^a JORDAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Jordan)

Author keywords

Fuzzy inference system; Hybrid prediction model; Protein contact map prediction

Indexed keywords

3D STRUCTURE; ACCURATE PREDICTION; ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM; CONTACT MAPS; DATA SETS; EXPERIMENTAL METHODS; FILTERING OPERATIONS; FUZZY INFERENCE SYSTEMS; HYBRID INTELLIGENCE; HYBRID PREDICTION MODELS; INFERENCE SYSTEMS; K-NEAREST NEIGHBORS; MULTI-STAGE; PROTEIN FUNCTIONS; PROTEIN SEQUENCES; SEPARATION DISTANCES; TRAINING DATASET; WINDOW SIZE;

AMINO ACIDS; EXPERT SYSTEMS; FORECASTING; FUZZY INFERENCE; FUZZY SYSTEMS; MATHEMATICAL MODELS; STATISTICAL TESTS; THREE DIMENSIONAL;

PROTEINS;

ACCURACY; ALPHA HELIX; AMINO ACID SEQUENCE; ARTICLE; BETA SHEET; EXPERIMENTAL STUDY; FUZZY SYSTEM; HYBRID; IMAGE RECONSTRUCTION; INTELLIGENCE; PREDICTIVE VALUE; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEIN FUNCTION; PROTEIN SECONDARY STRUCTURE; SEPARATION TECHNIQUE; STRUCTURE ANALYSIS; THREE DIMENSIONAL IMAGING;

ALGORITHMS; AMINO ACID SEQUENCE; AMINO ACIDS; DATABASES, PROTEIN; FUZZY LOGIC; PROTEIN CONFORMATION; PROTEINS;

EID: 84856366339     PISSN: 15320464     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jbi.2011.10.008     Document Type: Article

References (34)

1. Rost B. Protein structure prediction in 1D, 2D, and 3D. The Encyclopedia of Computational Chemistry; 1998. p. 2242-55.
2. Gupta N., Mangal N., Biswas S. Evolution and similarity evaluation of protein structures in contact map space. Proteins: Struct, Funct, Bioinform 2005, 59:196-204. 10.1002/prot.20415.
3. Geerlof A., et al. The impact of protein characterization in structural proteomics. Acta Crystallogr 2006, ISSN 0907-4449.
4. M Tyszka J., E Fraser S., E Jacobs R. Magnetic resonance microscopy: recent advances and applications. Curr Opin Biotechnol 2005, 16(1):93-99.
5. Murzin Alexey G., Brenner Steven E., Hubbard Tim, Chothia Cyrus SCOP: a structural classification of proteins database for the investigation of sequences and structures. J Mol Biol 1995, 536-540.
6. Vendruscolo M., Kussell E., Domany E. Recovery of protein structure from contact maps. Fold Des 1997, 2:295-306.
7. Aszodi A., Gradwell M., Taylor W. Global fold determination from a small number of distance restraints. J Mol Biol 1995, 251:308-326.
8. Skolnick J., Kolinski A., Ortiz A: MONSSTER: a method for folding globular proteins with a small number of distance restraints. J Mol Biol 1997, 265:217-241.
9. Jianlin Cheng, Pierre Baldi Improved residue contact prediction using support vector machines and a large feature set. BMC Bioinform 2007, 8:113.
10. Pollastri G., Baldi P. Prediction of contact maps by recurrent neural network architectures and hidden context propagation from all four cardinal corners. Bioinformatics 2002, 18(Suppl. 1):S62-S70.
11. Marco Punta, Burkhard Rost PROFcon: novel prediction of long-range contacts. Bioinformatics 2005, 2960-2968.
12. http://predictioncenter.org/casp9/domain_definitions.cgi.
13. Zhang Y. Progress and challenges in protein structure prediction. Curr Opin Struct Biol 2008, 18(3):342-348.
14. Alessandro Vullo, Ian Walsh, Gianluca Pollastri A two-stage approach for improved prediction of residue contact maps. BMC Bioinform 2006, 7:180.
15. http://predictioncenter.org/casp9/doc/presentations/CASP9_RR.pdf.
16. Gobel U., Sander C., Schneider R., Valencia A. Correlated mutations and residue contacts in proteins. Proteins 1994, 18:309-317.
17. Klir George J., Yuan Bo Fuzzy sets and fuzzy logic: theory and applications 1995, Prentice Hall. 1st ed.
18. Jang J.-S.R., Sun C.-T., Mizutani E. Neuro-Fuzzy Soft Comput 1998.
19. Shakhnarovish, Darrell, Indyk Nearest-neighbor methods in learning and vision: theory and practice 2005, The MIT Press.
20. Frishman D., Argos P. Knowledge-based protein secondary structure assignment. Proteins 1995, 23(4):566-579.
21. Pauling L., Corey R.B., Branson H.R. The structure of proteins: two hydrogen-bonded helical configurations of the polypeptide chain. Proc Natl Acad Sci Wash 1951, 37:205.
22. http://predictioncenter.org/.
23. http://predictioncenter.org/casp7/meeting/presentations/Presentations_assessors/CASP7_RR_Clarke.pdf.
24. http://cubic.bioc.columbia.edu/eva/.
25. Burkhard R., Eyrich V.A. EVA: large-scale analysis of secondary structure prediction. Proteins: Struct, Funct, Genet 2001, (Suppl. 5):192-199.
26. Atomic Coordinate Entry Format Version 3.2. wwPDB, October 2008. http://www.wwpdb.org/documentation/format32/v3.2.html.
27. Gorodkin J., et al. Using sequence motifs for enhanced neural network prediction of protein distance constraints. Int Conf Intell Syst Mol Biol 1999, 95-105.
28. Altschul S.F., Gish W., Miller W., Myers E.W., Lipman D.J. Basic local alignment search tool. J Mol Biol 1990, 215(3):403-410.
29. Altschul S.F., et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 1997, 25:3389-3402.
30. Rost B. PROF: predicting one-dimensional protein structure by profile based neural networks. http://cubic.bioc.columbia.edu/pp/doc/methodsPP.html.
31. Pascual-Montano A., Carmona-Saez P., Chagoyen M., Tirado F., Carazo J.M., Pascual-Marqui R.D. bioNMF: a versatile tool for non-negative matrix factorization in biology. BMC Bioinform 2006, 7:366.
32. Lee D.D., Seung H.S. Learning the parts of objects by non-negative matrix factorization. Nature 1999, 401:788-791.
33. Chiu S. Fuzzy model identification based on cluster estimation. J Intell Fuzzy Syst 1994.
34. Yager R., Filev D. Generation of fuzzy rules by mountain clustering. J Intell Fuzzy Syst 1994.